Merge branch 'main' of https://github.com/microsoft/Data-Science-For-Beginners

4-Data-Science-Lifecycle/16-communication/README.md

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 # The Data Science Lifecycle: Communication
 
+|![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/16-Communicating.png)|
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+| Data Science Lifecycle: Communication - _Sketchnote by [@nitya](https://twitter.com/nitya)_ |
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 ## [Pre-Lecture Quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/30)
 
 Test your knowledge of what's to come with the Pre-Lecture Quiz above!

5-Data-Science-In-Cloud/17-Introduction/README.md

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 # Data Science in the Cloud: in progress
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+|![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/17-DataScience-Cloud.png)|
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+| Data Science In The Cloud: Introduction - _Sketchnote by [@nitya](https://twitter.com/nitya)_ |
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 In this lesson, you will learn the fundamental principles of the Cloud, then you will see why it can be interesting for you to use Cloud services to run your data science projects and we'll look at some examples of data science projects run in the Cloud. 
 
 

5-Data-Science-In-Cloud/18-Low-Code/README.md

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 # Data Science in the Cloud: The "Low code/No code" way 
 
+|![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/18-DataScience-Cloud.png)|
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+| Data Science In The Cloud: Low Code - _Sketchnote by [@nitya](https://twitter.com/nitya)_ |
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 Table of contents:
 
 - [Data Science in the Cloud: The "Low code/No code" way](#data-science-in-the-cloud-the-low-codeno-code-way)

5-Data-Science-In-Cloud/19-Azure/README.md

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 # Data Science in the Cloud: The "Azure ML SDK" way 
 
+|![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/19-DataScience-Cloud.png)|
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+| Data Science In The Cloud: Azure ML SDK - _Sketchnote by [@nitya](https://twitter.com/nitya)_ |
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 Table of contents:
 
 - [Data Science in the Cloud: The "Azure ML SDK" way](#data-science-in-the-cloud-the-azure-ml-sdk-way)

README.md

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 **Hearty thanks to our authors:** Jasmine Greenaway, Dmitry Soshnikov, Nitya Narasimhan, Jalen McGee, Jen Looper, Maud Levy, Tiffany Souterre, Christopher Harrison.
 
+|![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](./sketchnotes/00-Title.png)|
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+| Data Science For Beginners - _Sketchnote by [@nitya](https://twitter.com/nitya)_ |
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 # Getting Started
 
 > **Teachers**, we have [included some suggestions](for-teachers.md) on how to use this curriculum. We'd love your feedback [in our discussion forum](https://github.com/microsoft/Data-Science-For-Beginners/discussions)!
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 ## Lessons
 
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+|![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](./sketchnotes/00-Roadmap.png)|
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+| Data Science For Beginners: Roadmap - _Sketchnote by [@nitya](https://twitter.com/nitya)_ |
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 | Lesson Number | Topic | Lesson Grouping | Learning Objectives | Linked Lesson | Author |
 | :-----------: | :----------------------------------------: | :--------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------: | :----: |
 | 01 | Defining Data Science | [Introduction](1-Introduction/README.md) | Learn the basic concepts behind data science and how it’s related to artificial intelligence, machine learning, and big data. | [lesson](1-Introduction/01-defining-data-science/README.md) [video](https://youtu.be/pqqsm5reGvs) | [Dmitry](http://soshnikov.com) |